AI/ML Platform Engineer

We are a dynamic centralized platform team dedicated to harnessing cutting-edge AI/ML technology, particularly in the realm of Generative AI and large language models, to empower HP and drive innovation. Collaborating closely with various business units, we provide strategic advice, prototype solutions, and develop and manage software applications tailored for internal use.

Days split roughly evenly between hands-on building and collaboration/enablement, driven by a mix of roadmap work and incoming requests. Expect to shift context often.

• Internal platform tools and services: self-service portals/workbenches, backend APIs (Python/FastAPI), automations and CI/CD tooling
• MCP/gateway integrations and AI-enabled automations and flows
• Focus is always on reducing friction for teams adopting the platform

• Writing and maintaining Terraform; provisioning and configuring platform resources across AWS and Azure
• Diagnosing deployment, networking, endpoint, and configuration issues
• Enough depth to reason about deployments and partner with security/networking specialists

• Standups, syncs, and planning/project meetings
• Design and architecture reviews; regular PR and code review
• Onboarding new teams; translating ambiguous requirements into practical plans and challenging weak designs

• Helping teams productionize models—hosting options, inference patterns, scaling, cost, and operational readiness across SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes

• Documentation, onboarding guides, and reference examples
• Ad-hoc process and platform improvements—spotting and fixing rough edges proactively

• Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically has 7-10 years of work experience, preferably in computer programming languages, machine learning, algorithms, statistical methods, or a related field.

AWS Certified Machine Learning Specialty

• Agile Methodology

• Algorithms

• Amazon Web Services

• Apache Spark

• Artificial Intelligence

• Automation

• Big Data

• C++ (Programming Language)

• Computer Science

• Data Science

• Deep Learning

• Java (Programming Language)

• Machine Learning

• Microsoft Azure

• Natural Language Processing

• Python (Programming Language)

• PyTorch (Machine Learning Library)

• Scikit-learn (Machine Learning Library)

• Software Engineering

• TensorFlow

• Effective Communication

• Results Orientation

• Learning Agility

• Digital Fluency

• Customer Centricity

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

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